TN2 Webinar on Systems & Network Neurosciences
Date: June 30, 2022
Time: 12:15-13:30 (CEST)
Location: Online via Zoom
Registration: https://us06web.zoom.us/webinar/register/WN_rgBzGeVrRBWIY612lHVySQ
Program (12:15-13:30)
- Welcome and introduction
- Presentation by Eus van Someren (VU Amsterdam, Amsterdam UMC & NIN)
- Presentation by Willem de Haan (Amsterdam UMC)
- Plenary wrap up
Eus van Someren, Head of the Department of Sleep & Cognition, Netherlands Institute for Neuroscience; Professor Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU Amsterdam; Amsterdam UMC
Title: Sleep on it to ditch or deepen distress: why insomnia is the primary modifiable risk for emotional disorders
Short abstract: Reactivation and synaptic plasticity in engrams or memory traces of prior wake experiences during subsequent sleep supports consolidation and adaptation of skills and episodic memory. It has largely been ignored that the sleep-facilitated synaptic plasticity processes also alter limbic, autonomic and behavioral responses embedded in engrams of distressing experiences. Even less considered is that the success of these processes determines the severity of emotional distress experienced with subsequent encounters with reoccurring identical or similar stimuli and contexts. This presentation gives clues on why sleep makes distress disappear overnight in good sleepers, yet fails to do so or can even be maladaptive by worsening distress overnight in insomnia, thus becoming the primary risk factor for emotional disorders. New insights call for moving insomnia research from psychology to the level of neuronal circuit-, cellular- and synaptic adaptations in order to understand and intervene on the most prevalent and burdening mental disorders.
Willem de Haan, neurologist and postdoctoral researcher, Alzheimer Center Amsterdam, Amsterdam UMC
Title: How to fight Alzheimer’s disease with computational brain network models
Short abstract: This presentation will show the power and versatility of computational brain network modeling when applied to neurophysiology in Alzheimer’s disease (AD). Computational models can help to understand the complex dynamics of the brain and its disturbance in AD, but can also be employed to simulate disease damage mechanisms or treatment targeting brain activity (e.g. transcranial electrical stimulation). The multiscale nature of so-called neural mass models also enables us to link cellular pathology (e.g. amyloid-induced) to neuronal circuit and large-scale network abnormalities, as observed in human EEG/MEG data. This presentations show how this might help to establish a coherent description of the neurophysiological disease mechanism, and how this can point towards new therapeutic targets.
